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Title: Performance Comparison of Knowledge-Based Dose Prediction Techniques Based on Limited Patient Data

Journal Article · · Technology in Cancer Research & Treatment
ORCiD logo [1];  [1];  [2];  [1];  [1]
  1. Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, USA
  2. Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
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Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
SC0017057
OSTI ID:
1481434
Journal Information:
Technology in Cancer Research & Treatment, Journal Name: Technology in Cancer Research & Treatment Vol. 17; ISSN 1533-0346
Publisher:
SAGECopyright Statement
Country of Publication:
United States
Language:
English

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Stereotactic Ablative Radiation Therapy for Centrally Located Early Stage or Isolated Parenchymal Recurrences of Non-Small Cell Lung Cancer: How to Fly in a “No Fly Zone” journal April 2014
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A planning quality evaluation tool for prostate adaptive IMRT based on machine learning: Planning quality evaluation tool for adaptive radiotherapy journal January 2011
Quantitative analysis of the factors which affect the interpatient organ-at-risk dose sparing variation in IMRT plans: Interpatient organ sparing variation modeling in IMRT plans journal October 2012
Predicting dose-volume histograms for organs-at-risk in IMRT planning: Predicting DVHs for OARs in IMRT planning journal November 2012
Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy: Knowledge-based prediction of 3D dose distributions journal December 2015
LIBSVM: A library for support vector machines journal April 2011
Feasibility of extreme dose escalation for glioblastoma multiforme using 4π radiotherapy journal November 2014
Treatment planning comparison of IMPT, VMAT and 4π radiotherapy for prostate cases journal January 2017
Predicting liver SBRT eligibility and plan quality for VMAT and 4π plans journal April 2017

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